The AI Software Dev Platform Built for Bitbucket and Jira

Engineering teams that rely on Bitbucket and Jira already operate with structure, clarity, and control. Tabnine brings AI into that environment—natively—so teams can accelerate delivery without sacrificing the integrity of their tools, processes, or codebase.

Tabnine connects directly to your Bitbucket repositories and Jira workflows. It enables your developers to write, review, test, and maintain code with the support of trusted AI—within the platforms they already use every day.

This is AI that integrates into the Atlassian stack by design. It works with your source of truth and enforces your standards. It meets your team in the IDE, understands the structure of your code, and aligns to the way your organization builds.

Made for the Atlassian ecosystem

Tabnine integrates with Bitbucket and Jira at the core platform level—not just through extensions or plugins. That means every agent, every suggestion, every AI pair programmer interaction is grounded in your actual code and planning context.

When connected to Bitbucket, Tabnine continuously indexes your repositories using real-time semantic and graph-based techniques. It maps relationships between services, functions, and files so it can retrieve relevant context during coding, testing, and review. Developers can scope their interactions down to specific folders or files for precision, and every suggestion is grounded in real project context.

With the Jira to Code Agent, developers can turn structured Jira tickets into structured code. Tabnine connects requirements to implementation by linking story-level context with the relevant Bitbucket repositories, helping teams move from planning to production with consistency.

Together, these integrations make Tabnine the most aligned AI platform for teams operating inside the Atlassian ecosystem. This is AI that fits your environment, speaks your language, and respects your workflows.

Controlled. Grounded. Secured.

Tabnine is built for engineering teams that work in regulated environments, operate at scale, and expect precision from every system in their stack.

Controlled: Developers get complete visibility into what Tabnine suggests and why. Every recommendation includes references, explanations, and validation checks.

→ Nothing ships without developer approval.

Grounded: Tabnine adapts to your environment, aligns with your codebase, and enforces your organization’s standards—from architecture and code quality to compliance and security. Guardrails are built in and enforced at every step.

→ AI onboards to your organization.

Secured: Tabnine runs wherever you need it to: SaaS, VPC, on-premises, or air-gapped. Your source code stays inside your perimeter. Your data stays yours.

→ Your code stays where it belongs.

The Enterprise Context Engine: How Tabnine onboards AI to your organization

At the core of Tabnine is the Enterprise Context Engine—a system purpose-built to bring structure, explainability, and safety to AI-assisted development inside of Tabnine.

Tabnine continuously ingests real-time context from your codebase, workspace, and supporting documentation—so the AI always reflects the current state of your system, not last week’s assumptions. It maps the architecture of your software using graph-based models, allowing it to understand relationships between services, components, and dependencies—so every suggestion respects how your system is actually built.

Through intelligent retrieval, Tabnine identifies the most relevant context for each task—surfacing the right information at the right moment, without noise or guesswork. And it gives developers control when they need it.  Developers can scope context with precision—down to the repository, file, or even function—so the AI works within clearly defined boundaries and doesn’t overreach.

Every output is validated against your organization’s standards for quality, security, and maintainability—ensuring the AI doesn’t just generate code, it generates the right code. And with centralized governance, admin-level policies, and usage analytics, you maintain full oversight—so AI adoption aligns with your security posture, compliance frameworks, and engineering objectives.

Any AI can run inside an environment. What makes Tabnine different is it understands what your developers need to build, what already exists, how it fits together, and how it needs to be done. That’s what we mean by AI that’s onboarded into your organization.

Improve what you’ve already built

With Tabnine, you don’t replace your existing stack—you unlock more from it.

• Accelerate modernization projects in Bitbucket

• Reduce tech debt and increase test coverage

• Validate changes with precision during code review

• Connect planning to implementation through Jira and context-aware agents

No context switching. No retraining. No disruption.

Just better outcomes—delivered through the systems your teams already trust.

See it in action

Tabnine Enterprise includes full native support for Bitbucket and Jira.

Join our next live session or request a tailored walkthrough to see how engineering leaders are using Tabnine to bring AI into every step of the SDLC—with control, clarity, and confidence.

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